International Business Machines Corporation
QUANTIFYING MACHINE LEARNING MODEL UNCERTAINTY

Abstract:

Evaluating machine learning model classifications, training a machine learning classification model using a training data set from a first data distribution, determining a classification for test data from a second data distribution using the machine learning classification model, wherein the first data distribution and the second data distribution are disjoint distributions, determining an uncertainty for the classification of the test data according to a difference between the first data distribution and the second data distribution.